Methods, systems, and apparatus for identification, characterization, and treatment of rotors associated with fibrillation

ABSTRACT

Some embodiments described herein relate to a method that includes defining an electro-anatomical model of a heart. The electro-anatomical model can include conduction patterns for multiple patterns or phases identified by a measurement instrument. The electro-anatomical model can also include a voltage map of the heart. A portion of the heart containing a rotor can be identified based on circulation in one phase of the model. The rotor can be determined to be stable based on that portion of the heart having circulation in another phase of the model. The rotor can be characterized as a substrate rotor based on the rotor being stable and based on the voltage or a change in voltage at the portion of the heart containing the rotor. The rotor can be treated or ablated when the rotor is determined to be a substrate rotor.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of provisional U.S. PatentApplication No. 61/988,651, filed May 5, 2014, under 35 U.S.C. §119(e),the disclosure of which is hereby incorporated by reference in itsentirety.

BACKGROUND

This application relates generally to methods, systems, and apparatusfor identifying, characterizing, and treating rotors associated withfibrillation. Some methods described herein are suitable fordistinguishing between and/or classifying substrate rotors andnon-substrate rotors. Substrate rotors may be associated with and/or maysignificantly influence arrhythmias, while non-substrate rotors may notbe strongly associated with arrhythmias. Some embodiments describedherein can include treating substrate rotors and/or not treatingnon-substrate rotors, which can improve cardiac outcomes.

In the last few years, scientific understanding of atrial fibrillationhas discovered that the electrical activity in the heart during atrialfibrillation is not complete chaos as once accepted under the Moe modelof random wavelets of electrical activity causing atrial fibrillation.There are indeed local organized electrical drivers of atrialfibrillation. Recent research has revealed that electrical patterns inthe heart commonly referred to as rotors play an important role in manycases of fibrillation, particularly persistent atrial fibrillation.Currently, surgical systems are available that modify cardiac tissueduring treatment using RF energy, cryo, laser, direct current,stem-cells, or drugs. In some situations modifying, ablating, or“burning” a rotor can significantly improve cardiac function.

Known surgical techniques, however, have inconsistent results; ablationof some rotors results in significant changes in heart rhythm, whileablation of other rotors does not have a significant effect. A needtherefore exists for methods, systems, and apparatus for identifying andcharacterizing rotors.

SUMMARY

Some embodiments described herein relate to a method that includesdefining an electro-anatomical model of a heart. The electro-anatomicalmodel can include conduction patterns for multiple patterns or phasesidentified by a measurement instrument. The electro-anatomical model canalso include a voltage map of the heart. A portion of the heartcontaining a rotor can be identified based on circulation in one phaseof the model. The rotor can be determined to be stable based certaincharacteristics including stability of the rotor over time and/or acrossphases, the rotor presenting along borders of voltage transition, and/ornegative association with complex fractionated electrograms in theregion of the rotor's presentation. The rotor can be treated or ablatedwhen the rotor is determined to be a substrate rotor.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic block diagram of a system for classifying and/ortreating rotors.

FIG. 2 is a flow chart of a method of treating a cardiac arrhythmia,according to an embodiment.

FIGS. 3A and 3B are two phases of an example of an electro-anatomicalmodel of a left atrium showing cardiac conduction patterns, according toan embodiment.

FIG. 3C is an example of an electro-anatomical model of the left atriumof FIGS. 3A and 3B showing a voltage map.

FIG. 3D is an example of an electro-anatomical model of the left atriumof FIGS. 3A-3C showing a complex fractionation map.

FIG. 4A is an example of an electro-anatomical model of a left atriumshowing conduction patterns.

FIG. 4B is an example of an electro-anatomical model of the left atriumof FIG. 4A showing a voltage map.

FIG. 5 is a flow chart of a method for classifying rotors, according toan embodiment.

DETAILED DESCRIPTION

Some embodiments described herein relate to an apparatus including aninput module, a model module, and a rotor characterization module. Theinput module can be operable to receive data from a sensor and/orelectrode disposed within a heart of a patient. The model module candefine an electro-anatomical model of the heart or a portion thereofbased on signals received from the sensor and/or electrode. Theelectro-anatomical model can include a map of tissue voltages and a mapof complex electrogram fractionation. The rotor characterization modulecan be operable to characterize a rotor as a substrate rotor or anon-substrate rotor based on the electro-anatomical model. Thecharacterization can be based on some combination of rotor stability,the map of tissue voltages, and the map of complex electrogramfractionation.

Some embodiments described herein relate to a method that includesdefining an electro-anatomical model of a heart. The electro-anatomicalmodel can include conduction patterns for multiple patterns or phasesidentified by a measurement instrument. The electro-anatomical model canalso include a voltage map of the heart. A portion of the heartcontaining a rotor can be identified based on circulation in one phaseof the model. The rotor can be determined to be stable based on certaincharacteristics, including the rotor being stable over time. Forexample, the rotor can be considered stable if circulation appears inmultiple phases of the electro-anatomical model. The rotor can becharacterized as a substrate rotor based on the rotor being the voltageor a change in voltage at the portion of the heart containing the rotor.For example, the rotor presenting along borders of voltage transition,which can be associated with healthy cardiac tissue meeting scar tissue,can be considered when evaluating a rotor. Furthermore, in someinstances, complex fractionated electrograms in the region of the rotorspresentation can be evaluated. Complex fractionated electrograms can benegatively associated with substrate rotors. The rotor can be treated orablated when the rotor is determined to be a substrate rotor.

Some embodiments described herein relate to a method that includesdefining an electro-anatomical model of a heart. The electro-anatomicalmodel can include conduction patterns for multiple patterns or phasesidentified by a measurement instrument. The electro-anatomical model canalso include a complex fractionated electrogram map of the heart. Aportion of the heart containing a rotor can be identified based oncirculation in one phase of the model. The rotor can be determined to beunstable based on that portion of the heart not having circulation inanother phase of the conduction model. The rotor can be characterized asa substrate rotor based on the rotor being stable and based on thedegree of complex fractionation of the electrogram at the portion of theheart containing the rotor. The rotor can be treated or ablated based onthe rotor being a substrate rotor.

FIG. 1 is a schematic block diagram of a system 100 for measuring,detecting, classifying, and/or treating cardiac arrhythmias, accordingto an embodiment. The system 100 includes a compute device 110 and animaging device 150. The compute device 110 can operably coupled to apatient 150, e.g., via a sensor 120, and/or the imaging device 150.

The system 100 can also include an instrument 130 configured to bedisposed within the heart 145. The instrument 130 can be operable tomodify, ablate, and/or burn tissue (e.g., cardiac tissue), for example,to treat atrial fibrillation. In some instances, the instrument 130 canbe directed, in whole or in part, by the compute device 110. Forexample, the compute device 110 can be operable to actuate a portion(e.g., a tip) of the instrument 130 to modify tissue, steer theinstrument 130, and so forth. In some instances, the compute device 110can be operable to provide directions, instructions, and/or data to anoperator of the instrument 130 to aid the operator (e.g., a surgeon) incontrolling the instrument 130.

The imaging device 150 can be any suitable medical or other imagingdevice, such as an x-ray device, an ultrasound, magnetic resonanceimaging (MRI) device, and/or computerized tomography (CT) imagingdevice. The imaging device can be operable to image the patient 140, ora portion thereof, such as a heart 145 of the patient 140. In someembodiments, the imaging device 150 can be operable to conductmeasurements and process imaging data. For example, the imaging device150 can include a processor and/or a memory (not shown) which can bestructurally and/or functionally similar to a processor 112 and/or amemory 114 of the compute device 110, described in further detailherein.

In some embodiments, the imaging device 150 can be configured to imagethe heart 145, a chamber of the heart 145, such as an atrium 148, and/orthe sensor 120, for example, within the heart 145. In such anembodiment, the imaging device 150 can be operable to localize thesensor 120 within the heart 145. For example, the imaging device 150 canbe operable to identify the position of the sensor 120 while the sensor120 is used to sense electrical or other signals from cardiac tissue. Inthis way, data received from the sensor 120 can be mapped to specificpoints and/or areas of the heart 145.

The sensor 120 can be can be a loop catheter with one or more electrodes124, a basket catheter with one or more electrodes 124, or another typeof single- or multi-electrode device capable of sensing cardiacelectrical activity locally at particular sites within the heart 145. Insome embodiments, the sensor 120 can be a basket catheter designed tofill a heart chamber (e.g., an atrium 148). In other embodiments thesensor 120 can be a basket catheter designed to partially fill a heartchamber. In yet other embodiments, the sensor 120 can be a star shapedcatheter.

In some embodiments, the sensor 120 can be or include a near-fieldmeasurement instrument having an integrated electromagnetic sensor (notshown) such that the near-field measurement instrument can be localizedby a tracking system. The near-field measurement instrument can rove aportion of the patient's 140 anatomy, such as an atrium 148 (e.g., inatrial fibrillation). The near-field measurement instrument can belocalized by any suitable tracking system such as tracking systems thatutilize electropotential, impedance, or other technologies. For example,the tracking system any of the systems disclosed in United States PatentApplication Publication No. 2013/0267835 to Edwards, entitled “Systemand Method for Localizing Medical Instruments during CardiovascularMedical Procedures,” the disclosure of which is hereby incorporated byreference in its entirety.

In some embodiments, the sensor 120 can be or include a far-fieldmeasurement instrument such as a coronary sinus catheter or multipleelectrodes placed on the body surface of the patient 140 with thecapability of sensing cardiac electrical activity from a distance. Sucha far-field measurement instrument can be used to measure the patient's140 heart signal. The far-field measurement instrument can have anelectromagnetic sensor integrated into it such that the far-fieldmeasurement instrument can be localized by a tracking system. Thefar-field measurement instrument can also be localized by other trackingsystems that utilize electropotential, impedance, or other technologiesfor tracking.

The compute device 110 can be any suitable computing entity, such as adesktop computer, laptop computer, server, computing cluster, specialpurpose instrument, etc. The compute device 110 includes a processor112, a memory 114, an input module 115, an output module 116, a modelmodule 117, a rotor identification module 118, and a rotorcharacterization module 119, each of which can be operably and/orcommunicatively coupled to each other.

The processor 112 can be for example, a general purpose processor, aField Programmable Gate Array (FPGA), an Application Specific IntegratedCircuit (ASIC), a Digital Signal Processor (DSP), and/or the like. Theprocessor 112 can be configured to retrieve data from and/or write datato memory, e.g., the memory 114, which can be, for example, randomaccess memory (RAM), memory buffers, hard drives, databases, erasableprogrammable read only memory (EPROMs), electrically erasableprogrammable read only memory (EEPROMs), read only memory (ROM), flashmemory, hard disks, floppy disks, cloud storage, and/or so forth.

The input module 115 can be hardware and/or software (e.g., stored inthe memory 114 and/or executing on the processor 112) operable toreceive signals from any suitable input device. For example, the inputmodule 115 can be operable to receive data from the sensor 120associated with electrical features of the heart 145. The input module115 can further be operable to receive raw and/or pre-processed datafrom the imaging device 150. For example, as described in further detailherein, the input module 115 can be operable to receive data from theimaging device 150 such that the compute device 110 can construct amodel of the heart 145. The input module 115 can further be operable toreceive data from an instrument localization device (e.g., the imagingdevice 150 or any other suitable tracking system). For example, asdescribed in further detail herein, the input module 115 can be operableto receive data from an instrument localization device such that thecompute device 110 can associate data received from the instrument 120with a location at which a measurement was taken. In addition oralternatively, the input module 115 can be operable to receive data fromany other suitable input device such as a keyboard, a mouse, a touchscreen, etc.

The output module 116 can be hardware and/or software (e.g., stored inthe memory 114 and/or executing on the processor 112) operable to sendsignals from any suitable output device. For example, the output module116 can be operable to send signals to a monitor (not shown) or otherdisplay device to cause the monitor to present an electro-anatomicalmodel of the heart 145. As described in further detail herein, such anelectro-anatomical model can indicate the position of rotors and/or candistinguish between substrate and non-substrate rotors. Such a monitorpresenting such a graphical electro-anatomical model can be used by aclinician (e.g., a surgeon) to guide and/or direct a cardiacintervention or other procedure.

As another example, the output module 116 can be operably coupled to theinstrument 130 and can be operable to actuate the instrument 130 whenthe instrument 130 is in a position determined by the compute device 110to be associated with a substrate rotor (e.g., to ablate the rotor).Conversely, the output module 116 can be operable to refrain fromactuating the instrument 130 when the instrument 130 is in a positionnot associated with a rotor and/or determined by the compute device 110to be associated with a non-substrate rotor. Furthermore, in someembodiments, the output module 116 can be operable to control, steer,and/or direct the instrument 130 to a position determined by the computedevice 110 to be associated with a substrate rotor. In addition oralternatively, the output module 116 can be operable to send data to anyother suitable output device, such as an audible output device, a chartrecorder, a haptic feedback device (e.g., coupled to the instrument130), etc.

The model module 117, as described in further detail herein, can beoperable to generate an electro-anatomical model of a portion of thepatient's 140 anatomy, such as the heart 145 and/or an atrium 148. Themodel module 117 can be hardware and/or software (e.g., stored in thememory 114 and/or executing on the processor 112) operable to receiveand/or process data from the sensor 120, the imaging device 150, and/oran instrument tracking device (not shown) (e.g., via the input module115). The model module 117 can integrate electrical data received fromthe sensor 120, positional data received from the tracking device,and/or anatomical data received from the imaging device 150 to generatea unified and/or layered electro-anatomical model. In addition oralternatively, the model module 117 can be operable to define multipleelectro-anatomical models, for example, associated with differentelectric or anatomical features, such as voltage, conduction patterns,and/or complex electrogram fractionation.

The rotor identification module 118 can be hardware and/or software(e.g., stored in the memory 114 and/or executing on the processor 112)operable to process electrical and/or anatomical data pre-processed, forexample, by the model module 117. The rotor identification module 118,as described in further detail herein can be operable to identify thepresence and/or position of rotors. For example, the rotoridentification module 118 can be operable to identify swirling and/orspiral conduction patterns associated with rotors.

The rotor characterization module 119 can be hardware and/or software(e.g., stored in the memory 114 and/or executing on the processor 112)operable to process electrical and/or anatomical data pre-processed, forexample, by the rotor identification module 118 and/or the model module117. The rotor characterization module 119, as described in furtherdetail herein, particularly with reference to FIG. 5, can be operable toprocess rotor stability data, voltage data, complex fractionatedelectrograms (CFEs), and/or any other suitable date to characterize arotor as a substrate rotor or a non-substrate rotor.

FIG. 2 is a flow chart of a method of treating cardiac arrhythmia,according to an embodiment. In some instances, the method of FIG. 2 canbe a computer-implemented method, that is a method stored in anon-transitory memory and/or executing on a processor. For example, themethod of FIG. 2 can be executed by the compute device 110, shown anddescribed above with reference to FIG. 1.

At 210, cardiac imaging data can be received. The cardiac imaging datacan be data created from a cluster of two-dimensional (2D) orthree-dimensional (3D) points created by tracking an instrument (e.g.,the sensor 120) inside the heart as it is used to paint the interiorsurface of a chamber, and/or data from an imaging device (e.g., theimaging device 150). In some embodiments, the imaging data can besuitable to generate, define, and/or render a 3D model of the heart, forexample, using various linear and non-linear 3D registration techniques.In some embodiments, the imaging data can include time data such that afour-dimensional (4D) model of the heart can be generated, defined,and/or rendered. For example, a video, real-time, and/or animated modelof the heart can be created using the cardiac imaging data received, at210.

At 220, near- and/or far-field cardiac date (e.g., cardiac electrogram(EGM) data) can be received. For example, a near-field measurementinstrument (e.g., the sensor 120) can be used to measure a patient'sheart signal. The near-field measurement instrument can include and/orhave an electromagnetic sensor integrated into it such that thenear-field measurement instrument can be localized by a tracking system.In addition or alternatively, a far-field measurement instrument such asa coronary sinus catheter or multiple electrodes placed on the bodysurface of the patient with the capability of sensing cardiac electricalactivity from a distance can also be used to measure the patient's heartsignal. The far-field measurement instrument can include and/or have anelectromagnetic sensor integrated into it such that the far-fieldmeasurement instrument can be localized by a tracking system. Thefar-field measurement instrument can also be localized by other trackingsystems that utilize electropotential, impedance, or other technologiesfor tracking.

The near-field measurement instrument can capture EGM or other cardiacdata at various locations and/or positional data in x-y-z space, whichcan be received at 220 and integrated with the imaging data received at210. The near-field measurement data can be stored in a computer memory,database or other suitable device for storing data (e.g., the memory114). Furthermore, the far-field instrument can capture data associatedwith each near-field measured point, which can also be received at 220can also be integrated with the imaging data received at 210. Thefar-field data can also be stored in a computer memory, database, orother suitable device for storing data (e.g., the memory 114).

At 230, the electrogram data received, at 220 and the imaging datareceived, at 210 can be combined or integrated to define anelectro-anatomical model. For example, the model module 117 can beoperable to define an electro-anatomical model based on imaging datareceived at 210 and near-filed and/or positional data received at 220.The electro-anatomical model can be a 3D or 4D model of a heart or aportion thereof including a visualization (e.g., a vector field, heatmap, and/or any other suitable visualization) of electric potentials,conduction patterns or velocities, and/or any other suitableelectroanatomic feature, such as, for example, complex fractionatedelectrogram mapping.

FIGS. 3A-4B are examples of 3D left atrial electro-anatomical models.FIGS. 3A and 3B are two example phases of the electro-anatomical modelsof a left atrium showing cardiac conduction patterns. The conductionpatterns can cause contraction of heart muscle. As described in furtherdetail herein, a substrate based rotor 310, characterized by a swirlingconduction pattern, is indicated in the phase depicted in FIG. 3A aswell as in the phase depicted in FIG. 3B. A non-substrate based rotor320 is shown in FIG. 3A. The phase depicted in FIG. 3B does not indicatea swirling conduction pattern associated with rotor 320.

FIG. 3C is the left atrium of FIGS. 3A and 3B showing a voltage map ofthe left atrium. The voltage map of FIG. 3C highlights areas of healthytissue versus scar or unhealthy tissue. FIG. 3D is the left atrium ofFIGS. 3A-3C with a complex fractionated atrial electrogram map (CFAE).The CFAE map shown in FIG. 3D highlights areas having noisy (or high)fractionation of electrograms (EGMs) versus areas with lessfractionation of EGMs.

FIG. 4A is an electro-anatomical model of a left atrium showing cardiacconduction patterns. FIG. 4A depicts two non-substrate based rotors 420and one substrate based rotor 410 characterized by swirling conductionvectors. FIG. 4B is the left atrium of FIG. 4A showing a voltage maphighlighting borders of healthy tissue meeting scar or dead tissueresulting in voltage transition deltas. As described in further detailherein, the presence of rotor 410 in a voltage transition region 470 isindicative of rotor 410 being a substrate based rotor. Treatment(ablation) of the non-substrate based rotors 420 indicated by dots 465did not improve cardiac rhythm. Ablation of the substrate-based rotor410 indicated by dots 460 resulted in significant improvements in heartrhythm change and termination of atrial fibrillation.

Returning to FIG. 2, a control unit (e.g., the model module 117) canidentify patterns on the far-field data and index near-field cardiacelectrical data and near-field instrument position location informationto far-field data patterns at 230. The control unit can organize a setof near-field cardiac electrical data from multiple near-field positionlocations that display the same far-field data patterns. The controlunit can use this set of data and various interpolation techniques togenerate a 3D map of electrical activity for a region of the heartcorresponding to that far-field data pattern. This process can berepeated for multiple far-field data patterns to create multiple maps.The multiple 3D maps can be sequenced by the control unit into a 4D mapto show the various states of electrical conductivity of the heart overtime.

The 3D and/or 4D maps created can be superimposed on the model of thepatient's heart. The 3D maps can be displayed in 3D for visualizationwith bi-color glasses, polarized glasses, shuttered glasses, or anyother suitable viewing device that can be used to give true 3Dperspective to the viewer.

At 240, rotors can be identified (e.g., by the rotor identificationmodule 118). Rotors can be identified by any suitable technique. Forexample, rotors can be identified using a computational mappingalgorithm to, for example, integrate spatiotemporal wave front patternsduring atrial fibrillation on the electro-anatomical map defined, at230. For example, the computational mapping algorithm can search thesurface of the model defined 230 for complete rotation of conductionvelocity vectors. In some embodiments the complete surface of the modelcan be searched and one or more rotors can be identified. In someembodiments, when a rotor is identified, the region of rotationassociated with the rotor can be searched for additional rotations(e.g., partial and/or complete rotations), for example, over all phases.In addition or alternatively, voltage transition zones can be locatedand identified, for example, within a region of rotation. In someinstances, several rotors can be identified associated with a voltagetransition zone within a region of rotation. In some embodiments,information such as: (1) the number (or percent) of phases in which therotor is identified, (2) change in voltage at the region containing therotor and/or between the rotor and an adjacent region, and/or (3) degreeof complex fractionation for the region containing the rotor can becalculated and/or determined for each rotor.

At 250, rotors can be classified as substrate rotors or non-substraterotors (e.g., by the rotor characterization module 119). For example,rotors can be classified as shown and described in further detail hereinwith reference to FIG. 5. Rotors that are classified as substrate rotorscan be associated with causing and/or driving arrhythmias, while rotorsthat are classified as non-substrate rotors may not be associated withan arrhythmia.

Rotors classified as substrate rotors, at 250, can be selected fortreatment and/or treated, at 260. For example, substrate rotors can beablated. Treatment of substrate rotors, at 260, is strongly correlatedwith improved cardiac rhythms. Non-substrate rotors may not be treated,at 260. Treatment of non-substrate rotors is not correlated with, or isonly weakly correlated with improved cardiac rhythms. In an embodimentwhere only substrate rotors are treated, treatment time can be reducedand/or more cardiac tissue can be preserved as compared to an embodimentwhere substrate and non-substrate rotors are treated.

FIG. 5 is a decision tree 500 for classifying rotors, according to anembodiment. For example, the decision tree 500 can be used to classifyrotors as substrate or non-substrate rotors, at 250, as shown anddescribed above with reference to FIG. 2. In some instances, rotors canbe classified based on three criteria, stability, voltage change, andcomplex fractionation level. In some instances, rotors can also beclassified based on rotational patterns of wavefronts or any othersuitable feature. It should be appreciated that additional criteria canbe considered and/or different means can be employed to classify rotors.

At 510, a rotor can be evaluated for stability based, for example, ondetermining how many phases out of a total number of phases in which therotor appears. A phase can be a distinct pattern identified by afar-field electrogram measurement instrument. A rotor that presents in10% or more, 20% or more, 30% or more, 50% or more, or any othersuitable proportion of the total phases can be considered to be stable.

After evaluating for stability, at 510, rotors can be evaluated based onwhether they are in a voltage transition zone. A voltage transition zoneis a region of the heart characterized by a relatively large change inelectrical potential (high ΔV) over a relatively short distance. In somecases, a voltage transition zone can be a region of the heart where scartissue, which may be characterized by relatively low voltages, isdirectly adjacent to healthy tissue, which may be characterized byrelatively higher voltages. As measured in atrial fibrillation, a changeof greater than 0.5 mV, a change of greater than 0.23 mV, a change ofgreater than 0.2 mV, a change of greater than 0.1 mV, or any othersuitable threshold can be determined to be a high voltage transition. Avoltage transition zone can be associated with healthy tissue meetingdead or scarred tissue. As an illustration, rotor 310 is migrating alonga voltage transition zone, as shown in FIG. 4A, while rotor 320 is notdisposed in a voltage transition zone.

Rotors determined to be stable, at 510, are evaluated for voltagetransition, at 524. If a rotor is stable and in a voltage transitionzone, such as rotor 410, it can be classified as a substrate rotor.Rotors that are determined to be unstable, at 510, are evaluated forvoltage transition, at 526. If a rotor is unstable and not in a voltagetransition zone, such as rotor 320, the rotor can be classified as anon-substrate rotor.

If a rotor is stable and not in a voltage transition zone or unstableand in a voltage transition zone, at 534 or 536, respectively, complexfractionation (CFAE) level can be evaluated in the region in which therotor presents. Evaluating CFAE can include identifying, all peaks ofbipolar electrogram deflections which fall into the voltage window of0.05 to 0.15 mV, −0.05 to −0.15 mV, and those exceed +/−0.15 mV. Theintervals between two successive deflection peaks falling into thevoltage window of 0.05 to 0.15 mV or −0.05 to −0.15 mV can bedetermined. The CFAE level can be defined as the number of suchintervals between 70 ms and 120 ms in length during a 2.5 secondmeasurement. A CFAE level of 4, 5, 6, or any other suitable level can beconsidered to be high complex fractionation.

A stable rotor that does not present in a voltage transition zone, or anunstable rotor that presents in a voltage transition zone, with a lowcomplex fractionation can be classified as a substrate rotor at 534 or536. Conversely, such a rotor with high complex fractionation can beclassified as a non-substrate rotor at 534 or 536.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. Furthermore, although various embodiments have beendescribed as having particular features and/or combinations ofcomponents, other embodiments are possible having a combination of anyfeatures and/or components from any of embodiments where appropriate aswell as additional features and/or components.

Where methods described above indicate certain events occurring incertain order, the ordering of certain events may be modified.Additionally, certain of the events may be performed repeatedly,concurrently in a parallel process when possible, as well as performedsequentially as described above. Where methods are described above, itshould be understood that the methods can be computer implementedmethods having instructions stored on a non-transitory medium (e.g., amemory) and configured to be executed by a processor. For example, someor all of the events shown and described with reference to FIGS. 2and/or 5 can be implemented on a computer (e.g., the compute device110).

Some embodiments described herein relate to computer-readable medium. Acomputer-readable medium (or processor-readable medium) isnon-transitory in the sense that it does not include transitorypropagating signals per se (e.g., a propagating electromagnetic wavecarrying information on a transmission medium such as space or a cable).The media and computer code (also can be referred to as code) may bethose designed and constructed for the specific purpose or purposes.Examples of non-transitory computer-readable media include, but are notlimited to: magnetic storage media such as hard disks, floppy disks, andmagnetic tape; optical storage media such as Compact Disc/Digital VideoDiscs (CD/DVDs), Compact Disc-Read Only Memories (CD-ROMs), andholographic devices; magneto-optical storage media such as opticaldisks; carrier wave signal processing modules; and hardware devices thatare specially configured to store and execute program code, such asASICs, PLDs, ROM and RAM devices. Other embodiments described hereinrelate to a computer program product, which can include, for example,the instructions and/or computer code discussed herein.

Examples of computer code include, but are not limited to, micro-code ormicro-instructions, machine instructions, such as produced by acompiler, code used to produce a web service, and files containinghigher-level instructions that are executed by a computer using aninterpreter. For example, embodiments may be implemented using Java,C++, or other programming languages (e.g., object-oriented programminglanguages) and development tools. Additional examples of computer codeinclude, but are not limited to, control signals, encrypted code, andcompressed code.

What is claimed is:
 1. An apparatus, comprising: an input module, theinput module configured to receive data from an electrode disposedwithin a heart; a model module operably coupled to the input module, themodel module configured to define an electro-anatomical model of atleast a portion of the heart, the electro-anatomical model including amap of tissue voltages and a map of complex electrogram fractionationbased on signals received from the electrode; and a rotorcharacterization module operably coupled to the model module, the rotorcharacterization module configured to characterize a rotor as asubstrate rotor or a non-substrate rotor based on at least two of (1)rotor stability, (2) the map of tissue voltages at the rotor, and (3)the map of complex electrogram fractionation at the rotor.
 2. Theapparatus of claim 1, further comprising a rotor identification moduleoperably coupled to the model module, the rotor identification moduleconfigured to identify rotors based on conduction patterns from theelectro-anatomical model.
 3. The apparatus of claim 1, furthercomprising a rotor identification module operably coupled to the modelmodule, the rotor identification configured to identify rotors based onidentifying circulating conduction patterns from the electro-anatomicalmodel.
 4. The apparatus of claim 1, further comprising a rotoridentification module operably coupled to the model module, the rotoridentification module configured to identify a portion of the heartcontaining the rotor in a first phase of the electro-anatomical model,the rotor identification module configured to identify the rotor asunstable based on the rotor identification module not identifying therotor in the portion of the heart in a second phase of theelectro-anatomical model, the rotor characterization module configuredto characterize the rotor as a substrate rotor or a non-substrate rotorbased, in part, on the rotor being unstable.
 5. The apparatus of claim1, fin her comprising a rotor identification module operably coupled tothe model module, the rotor identification module configured to identifya portion of the heart containing the rotor in a first phase of theelectro-anatomical model, the rotor identification module configured toidentify the rotor as stable based on the identification moduleidentifying the rotor in the portion of the heart in a second phase ofthe electro-anatomical model, the rotor characterization moduleconfigured to characterize the rotor as a substrate rotor or anon-substrate rotor based, in part, on the rotor being stable.
 6. Theapparatus of claim 1, wherein the rotor characterization module isconfigured to identify the rotor as a substrate rotor based, at least inpart, on (1) the rotor being stable and (2) the rotor being in a highvoltage transition zone on the map of tissue voltages.
 7. The apparatusof claim 1, wherein the rotor characterization module is configured toidentify the rotor as a substrate rotor based, at least in part, on (1)the rotor being stable, (2) the rotor being in a low voltage transitionzone on the map of tissue voltages, and (3) the rotor being in a zone oflow complex fractionation on the map of complex electrogramfractionation.
 8. The apparatus of claim 1, wherein the rotorcharacterization module is configured to identify the rotor as anon-substrate rotor based, at least in part, on (1) the rotor beingstable, (2) the rotor being in a low voltage transition zone on the mapof tissue voltages, and (3) the rotor being in a zone of high complexfractionation on the map of complex electrogram fractionation.
 9. Theapparatus of claim 1, wherein the rotor characterization module isconfigured to identify the rotor as a non-substrate rotor based, atleast in part, on (1) the rotor being unstable, (2) the rotor being in ahigh voltage transition zone on the map of tissue voltages, and (3) therotor being in a zone of high complex fractionation on the map ofcomplex electrogram fractionation.
 10. The apparatus of claim 1, whereinthe rotor characterization module is configured to identify the rotor asa substrate rotor based, at least in part, on (1) the rotor beingunstable, (2) the rotor being in a high voltage transition zone on themap of tissue voltages, and (3) the rotor being in a zone of low complexfractionation on the map of complex electrogram fractionation.
 11. Theapparatus of claim 1, wherein the rotor characterization module isconfigured to identify the rotor as a non-substrate rotor based, atleast in part, on (1) the rotor being unstable, and (2) the rotor bringin a low voltage transition zone on the map of tissue voltages.
 12. Theapparatus of claim 1, further comprising an output module configured tosend a signal such that an optical display presents a visualization ofthe heart including a substrate rotor.
 13. The apparatus of claim 1,further comprising a surgical instrument configured to ablate asubstrate rotor.
 14. The apparatus of claim 13, wherein the surgicalinstrument is configured to not ablate a non-substrate rotor.
 15. Theapparatus of claim 1, wherein the input module is configured to receivedata from a plurality of electrodes of a roving medical instrumentdisposed within a heart chamber.
 16. The apparatus of claim 1, whereinthe input module is configured to receive data from the electrodedisposed within an atrium of the heart when the heart is in atrialfibrillation.
 17. A non-transitory processor readable medium storingcode representing instructions to be executed by a processor, the codecomprising code to cause the processor to: define an electro-anatomicalmodel of a heart including conduction patterns for a plurality of phasesof the heart and a voltage map; identify a portion of the heartcontaining a rotor based on circulation in a conduction pattern for afirst phase from the plurality of phases; identify the rotor as stablebased on circulation in a conduction pattern for be portion of the heartin a second phase from the plurality of phases; characterize the rotoras a substrate rotor based, at least in part, on (1) the rotor beingstable and (2) a change in voltage at the portion of the heart; and senda signal to cause the rotor to be treated based on the rotor being asubstrate rotor.
 18. The non-transitory processor readable medium ofclaim 17, wherein the code to cause the processor to identify the rotoras stable includes code to cause the processor to identify the rotor asstable based on circulation in conduction patterns for the portion ofthe heart in a subset of the plurality of phases, the subset of theplurality of phases including the first phase and the second phase, thesubset of the plurality of phases making up at least 30% of theplurality of phases.
 19. The non-transitory processor readable medium ofclaim 17, wherein there is a voltage change of at least 0.23 mV at theportion of the heart.
 20. The non-transitory processor readable mediumof claim 17, wherein: the electro-anatomical model of the heart furtherincludes a complex fractionated atrial electrogram map; and the rotor ischaracterized as a substrate rotor based on a voltage change of lessthan 0.23 my at the portion of the heart and the portion of the hearthaving low complex fractionation on the complex fractionated atrialelectrogram map.
 21. A method, comprising: defining anelectro-anatomical model of a heart including conduction patterns for aplurality of phases of the heart and a complex fractionated atrialelectrogram map; identifying a portion of the heart containing a rotorbased on circulation in a conduction pattern for a first phase from theplurality of phases; identifying the rotor as unstable based on a lackof circulation in a conduction pattern for the portion of the heart in asecond phase from the plurality of phases; characterizing the rotor as asubstrate rotor based, at least in part, on (1) the rotor being unstableand (2) the portion of the heart having low complex fractionation on thecomplex fractionated atrial electrogram map; and treating the rotorbased on the rotor being a substrate rotor.
 22. The method of claim 21,wherein: the electro-anatomical model of the heart further includes avoltage map; and the rotor is characterized as a substrate rotor based,in part, on a high change in voltage at the portion of the heart. 23.The method of claim 21, wherein treating the rotor includes ablating therotor.
 24. The method of claim 21, wherein the portion of the heartcontains a first rotor, and the electro-anatomical model of the heartfurther includes a voltage map the method further comprising:identifying a second portion of the heart containing a second rotor;characterizing the second rotor as a non-substrate rotor based on atleast two of (1) the stability of the second rotor, (2) the voltage mapat the second portion of the heart, and (3) the map of complexelectrogram fractionation at the second portion of the heart; and nottreating the second rotor based on the second rotor being characterizedas a non-substrate rotor.